Independent Component Analysis of Electroencephalogram

نویسندگان

  • Prabhakar K. Nayak
  • Niranjan U. Cholayya
چکیده

The analysis of electroencephalographic (EEG) recording is important both for brain research and for medical diagnosis and treatment. Independent Component Analysis (ICA) is an effective method for removing artifacts and separating sources of the brain signals from the EEG recordings. Results show that ICA is a useful technique for the evaluation of different variables in the brain activity.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Eliminating Electroencephalogram Artefacts Using Independent Component Analysis

The elimination of artefacts from Electroencephalogram(EEG) has an important role many signal and image processing applications. The artefacts are the noises that appears during the acquisition of signals from the patient body. With the presence of these artefacts it become difficult for doctors and technicians to analyse the Electroencephalogram signals efficiently. The aim of this research wo...

متن کامل

Efficiency Measurement of Clinical Units Using Integrated Independent Component Analysis-DEA Model under Fuzzy Conditions

Background and Objectives: Evaluating the performance of clinical units is critical for effective management of health settings. Certain assessment of clinical variables for performance analysis is not always possible, calling for use of uncertainty theory. This study aimed to develop and evaluate an integrated independent component analysis-fuzzy-data envelopment analysis approach to accurate ...

متن کامل

Comparison of Independent Component Analysis Algorithms for Removal of Ocular Artifacts from Electroencephalogram

The electroencephalogram (EEG) is useful for clinical diagnosis and in biomedical research. EEG recordings are distorted by electrooculogram (EOG) artifacts causing serious problem for EEG interpretation and analysis. An often preferable method is to apply Independent Component Analysis (ICA) to multichannel EEG recordings and remove a wide variety of artifacts from EEG recordings by eliminatin...

متن کامل

Alzheimer's detection using neural network techniques and enhanced EEG measurements

Electroencephalogram measurements of three “normal” (patients diagnosed as not having Alzheimer’s), and three “severe” (patients diagnosed as being in the late stages of Alzheimer’s) were analyzed using matrix operations, Independent Component Analysis, probability and Neural Network techniques [1]. There are several tests that can be administered to a patient to provide an accurate diagnosis o...

متن کامل

Performance Analysis of Epileptic Seizure Detection Using DWT & ICA with Neural Networks

The electroencephalogram (EEG) signal plays an important role in the detection of epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data and the detection of the epileptic activity requires a timeconsuming analysis of the entire length of the EEG data by an expert. The aim of this work is compare the automatic detection of EEG patterns using Discrete wavelet...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006